Musculoskeletal Diseases or Conditions
Conditions
Keywords
Motion Capture, MCA, Markers, Markerless, biomechanics
Brief summary
The investigators propose to create a markerless smartphone-based MCA application using AR to measure joint motion and gait patterns to address this technology gap for a simple and inexpensive MCA.
Detailed description
Aim 1 will establish a testable AR-based smartphone app that measures clinically relevant lower-extremity motion components. Existing AR code will be adapted to identify and quantify hip, knee, and ankle range of motion in both the coronal and sagittal planes. Output will be produced directly to the phone display and can also be downloadable. Both single-motion and sequential-motion (gait) measures will be captured. Aim 2 will then compare the app-based MCA to traditional gold standard MCA in healthy volunteers. A dedicated human biomechanics lab with capability for MCA with reflective markers will be utilized to test both MCA methods. Patients will perform a box jump and normal walking gait, and the measurements from both the standard marker-based MCA system and the smartphone markerless MCA system will be statistically compared.
Interventions
None listed
Sponsors
National Institutes of Health (NIH)
University of Arkansas
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
Yes
Inclusion criteria
* 18-65 years old * No known spinal pathology * No previous lower extremity surgery * No significant cardiac history
Exclusion criteria
* \<18 or \>65 years old * Known spinal pathology * Previous lower extremity surgery * Significant cardiac history
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Hip, Knee and Spine Measurements | 1 hour | angles |
Countries
United States
Outcome results
None listed